update the ads folder and setup.py

Author: z7ye

ads/ads_version.json

@@ -1,3 +1,3 @@
 {
-  "version": "2.8.1"
+  "version": "2.8.2"
 }

ads/automl/driver.py

@@ -1,16 +1,19 @@
 #!/usr/bin/env python
 # -*- coding: utf-8 -*--
 
-# Copyright (c) 2020, 2022 Oracle and/or its affiliates.
+# Copyright (c) 2020, 2023 Oracle and/or its affiliates.
 # Licensed under the Universal Permissive License v 1.0 as shown at https://oss.oracle.com/licenses/upl/
 
 from __future__ import absolute_import, division, print_function
 
+import copy
+
 import numpy as np
 import pandas as pd
 import scipy
-import copy
+
 from ads.common import logger, utils
+from ads.common.decorator.deprecate import deprecated
 from ads.common.model import ADSModel
 from ads.dataset import helper
 from ads.dataset.classification_dataset import (
@@ -37,6 +40,10 @@
 }
 
 
+@deprecated(
+    details="Working with AutoML has moved from within ADS to working directly with the AutoMLx library. AutoMLx are preinstalled in conda pack automlx_p38_cpu_v2 and later, and can now be updated independently of ADS. AutoMLx documentation may be found at https://docs.oracle.com/en-us/iaas/tools/automlx/latest/html/multiversion/v23.1.1/index.html. Notebook examples are in Oracle's samples repository: https://github.com/oracle-samples/oci-data-science-ai-samples/tree/master/notebook_examples and a migration tutorial can be found at https://accelerated-data-science.readthedocs.io/en/latest/user_guide/model_training/automl/quick_start.html .",
+    raise_error=True,
+)
 def get_ml_task_type(X, y, classes):
     """
     Gets the ML task type and returns it.
@@ -79,6 +86,10 @@ def get_ml_task_type(X, y, classes):
 
 
 class AutoML:
+    @deprecated(
+        details="Working with AutoML has moved from within ADS to working directly with the AutoMLx library. AutoMLx are preinstalled in conda pack automlx_p38_cpu_v2 and later, and can now be updated independently of ADS. AutoMLx documentation may be found at https://docs.oracle.com/en-us/iaas/tools/automlx/latest/html/multiversion/v23.1.1/index.html. Notebook examples are in Oracle's samples repository: https://github.com/oracle-samples/oci-data-science-ai-samples/tree/master/notebook_examples and a migration tutorial can be found at https://accelerated-data-science.readthedocs.io/en/latest/user_guide/model_training/automl/quick_start.html .",
+        raise_error=True,
+    )
     def __init__(
         self,
         training_data,
@@ -87,7 +98,7 @@ def __init__(
         baseline="dummy",
         client=None,
     ):
-        r"""
+        """
         Creates an Automatic machine learning object.
 
         Parameters

ads/automl/provider.py

@@ -1,7 +1,7 @@
 #!/usr/bin/env python
 # -*- coding: utf-8; -*-
 
-# Copyright (c) 2020, 2022 Oracle and/or its affiliates.
+# Copyright (c) 2020, 2023 Oracle and/or its affiliates.
 # Licensed under the Universal Permissive License v 1.0 as shown at https://oss.oracle.com/licenses/upl/
 
 import logging
@@ -41,6 +41,10 @@ class AutoMLProvider(ABC):
     implement train() and get_transformer_pipeline().
     """
 
+    @deprecated(
+        details="Working with AutoML has moved from within ADS to working directly with the AutoMLx library. AutoMLx are preinstalled in conda pack automlx_p38_cpu_v2 and later, and can now be updated independently of ADS. AutoMLx documentation may be found at https://docs.oracle.com/en-us/iaas/tools/automlx/latest/html/multiversion/v23.1.1/index.html. Notebook examples are in Oracle's samples repository: https://github.com/oracle-samples/oci-data-science-ai-samples/tree/master/notebook_examples and a migration tutorial can be found at https://accelerated-data-science.readthedocs.io/en/latest/user_guide/model_training/automl/quick_start.html .",
+        raise_error=True,
+    )
     def __init__(self):
         self.X_train = None
         self.y_train = None
@@ -143,6 +147,10 @@ class BaselineModel(object):
     interface. Labels (y) are encoded using DataFrameLabelEncoder.
     """
 
+    @deprecated(
+        details="Working with AutoML has moved from within ADS to working directly with the AutoMLx library. AutoMLx are preinstalled in conda pack automlx_p38_cpu_v2 and later, and can now be updated independently of ADS. AutoMLx documentation may be found at https://docs.oracle.com/en-us/iaas/tools/automlx/latest/html/multiversion/v23.1.1/index.html. Notebook examples are in Oracle's samples repository: https://github.com/oracle-samples/oci-data-science-ai-samples/tree/master/notebook_examples and a migration tutorial can be found at https://accelerated-data-science.readthedocs.io/en/latest/user_guide/model_training/automl/quick_start.html .",
+        raise_error=True,
+    )
     def __init__(self, est):
         self.est = est
         self.df_label_encoder = DataFrameLabelEncoder()
@@ -250,6 +258,10 @@ def get_transformer_pipeline(self):
         msg = "Baseline"
         return [("automl_preprocessing", AutoMLPreprocessingTransformer(msg))]
 
+    @deprecated(
+        details="Working with AutoML has moved from within ADS to working directly with the AutoMLx library. AutoMLx are preinstalled in conda pack automlx_p38_cpu_v2 and later, and can now be updated independently of ADS. AutoMLx documentation may be found at https://docs.oracle.com/en-us/iaas/tools/automlx/latest/html/multiversion/v23.1.1/index.html. Notebook examples are in Oracle's samples repository: https://github.com/oracle-samples/oci-data-science-ai-samples/tree/master/notebook_examples and a migration tutorial can be found at https://accelerated-data-science.readthedocs.io/en/latest/user_guide/model_training/automl/quick_start.html .",
+        raise_error=True,
+    )
     def __init__(self, est):
         """
         Generates a baseline model using the Zero Rule algorithm by default. For a classification
@@ -309,6 +321,7 @@ class OracleAutoMLProvider(AutoMLProvider, ABC):
     @deprecated(
         "2.6.7",
         details="Oracle AutoML is recommended to be directly instantiated by importing automlx package",
+        raise_error=True,
     )
     def __init__(
         self, n_jobs=-1, loglevel=None, logger_override=None, model_n_jobs: int = 1
@@ -870,6 +883,10 @@ def visualize_tuning_trials(self, ylabel=None):
 
 
 class AutoMLPreprocessingTransformer(object):  # pragma: no cover
+    @deprecated(
+        details="Working with AutoML has moved from within ADS to working directly with the AutoMLx library. AutoMLx are preinstalled in conda pack automlx_p38_cpu_v2 and later, and can now be updated independently of ADS. AutoMLx documentation may be found at https://docs.oracle.com/en-us/iaas/tools/automlx/latest/html/multiversion/v23.1.1/index.html. Notebook examples are in Oracle's samples repository: https://github.com/oracle-samples/oci-data-science-ai-samples/tree/master/notebook_examples and a migration tutorial can be found at https://accelerated-data-science.readthedocs.io/en/latest/user_guide/model_training/automl/quick_start.html .",
+        raise_error=True,
+    )
     def __init__(self, msg):
         self.msg = msg
 
@@ -915,6 +932,10 @@ def __repr__(self):
 
 
 class AutoMLFeatureSelection(object):  # pragma: no cover
+    @deprecated(
+        details="Working with AutoML has moved from within ADS to working directly with the AutoMLx library. AutoMLx are preinstalled in conda pack automlx_p38_cpu_v2 and later, and can now be updated independently of ADS. AutoMLx documentation may be found at https://docs.oracle.com/en-us/iaas/tools/automlx/latest/html/multiversion/v23.1.1/index.html. Notebook examples are in Oracle's samples repository: https://github.com/oracle-samples/oci-data-science-ai-samples/tree/master/notebook_examples and a migration tutorial can be found at https://accelerated-data-science.readthedocs.io/en/latest/user_guide/model_training/automl/quick_start.html .",
+        raise_error=True,
+    )
     def __init__(self, msg):
         self.msg = msg
 

ads/catalog/model.py

@@ -49,7 +49,7 @@
     OCI_REGION_METADATA,
     PROJECT_OCID,
 )
-from ads.dataset.progress import DummyProgressBar, TqdmProgressBar
+from ads.dataset.progress import TqdmProgressBar
 from ads.feature_engineering.schema import Schema
 from ads.model.model_version_set import ModelVersionSet, _extract_model_version_set_id
 from ads.model.deployment.model_deployer import ModelDeployer
@@ -1045,7 +1045,7 @@ def _download_large_artifact(
         model_id: str,
         target_dir: str,
         bucket_uri: str,
-        progress: Union[TqdmProgressBar, DummyProgressBar],
+        progress: TqdmProgressBar,
         remove_existing_artifact: Optional[bool] = True,
     ) -> None:
         """
@@ -1062,7 +1062,7 @@ def _download_large_artifact(
             The OCI Object Storage URI where model artifacts will be copied to.
             The `bucket_uri` is only necessary for downloading large artifacts with
             size is greater than 2GB. Example: `bucket_uri=oci://<bucket_name>@<namespace>/prefix/`.
-        progress: Union[TqdmProgressBar, DummyProgressBar]
+        progress: TqdmProgressBar
             The progress bar.
         remove_existing_artifact: (bool, optional). Defaults to `True`.
             Whether artifacts uploaded to object storage bucket need to be removed or not.
@@ -1125,7 +1125,7 @@ def _download_small_artifact(
         self,
         model_id: str,
         target_dir: str,
-        progress: Union[TqdmProgressBar, DummyProgressBar],
+        progress: TqdmProgressBar,
     ) -> None:
         """
         Downloads the model artifacts from model catalog to target_dir based on `model_id`.
@@ -1137,7 +1137,7 @@ def _download_small_artifact(
             The OCID of the model to download.
         target_dir: str
             The target location of model artifacts.
-        progress: Union[TqdmProgressBar, DummyProgressBar]
+        progress: TqdmProgressBar
             The progress bar.
 
         Returns
@@ -1422,9 +1422,7 @@ def upload_model(
             progress.update("Done")
         return self.get_model(model.data.id)
 
-    def _prepare_model_artifact(
-        self, model_artifact, progress: Union[TqdmProgressBar, DummyProgressBar]
-    ) -> str:
+    def _prepare_model_artifact(self, model_artifact, progress: TqdmProgressBar) -> str:
         """Prepares model artifacts to save in the Model Catalog.
 
         Returns

ads/common/auth.py

@@ -46,9 +46,10 @@ class AuthState(metaclass=SingletonMeta):
     oci_config_path: str = None
     oci_key_profile: str = None
     oci_config: str = None
-    oci_signer: str = None
-    oci_signer_callable: str = None
-    oci_signer_kwargs: str = None
+    oci_signer: Any = None
+    oci_signer_callable: Callable = None
+    oci_signer_kwargs: Dict = None
+    oci_client_kwargs: Dict = None
 
     def __post_init__(self):
         self.oci_iam_type = self.oci_iam_type or os.environ.get(
@@ -67,6 +68,7 @@ def __post_init__(self):
         self.oci_signer = self.oci_signer
         self.oci_signer_callable = self.oci_signer_callable
         self.oci_signer_kwargs = self.oci_signer_kwargs or {}
+        self.oci_client_kwargs = self.oci_client_kwargs or {}
 
 
 def set_auth(
@@ -77,6 +79,7 @@ def set_auth(
     signer: Optional[Any] = None,
     signer_callable: Optional[Callable] = None,
     signer_kwargs: Optional[Dict] = {},
+    client_kwargs: Optional[Dict] = {},
 ) -> None:
     """
     Save type of authentication, profile, config location, config (keypair identity) or signer, which will be used
@@ -101,6 +104,9 @@ def set_auth(
     signer_kwargs: Optional[Dict], default None
         parameters accepted by the signer.
         Check documentation: https://docs.oracle.com/en-us/iaas/tools/python/latest/api/signing.html
+    client_kwargs: Optional[Dict], default None
+        Additional keyword arguments for initializing the OCI client.
+        Example: client_kwargs = {"timeout": 60}
 
     Examples
     --------
@@ -110,6 +116,8 @@ def set_auth(
 
     >>> ads.set_auth("api_key", oci_config_location = "other_config_location") # use non-default oci_config_location
 
+    >>> ads.set_auth("api_key", client_kwargs={"timeout": 60}) # default signer with connection and read timeouts set to 60 seconds for the client.
+
     >>> other_config = oci.config.from_file("other_config_location", "OTHER_PROFILE") # Create non-default config
     >>> ads.set_auth(config=other_config) # Set api keys type of authentication based on provided config
 
@@ -149,7 +157,7 @@ def set_auth(
 
     auth_state.oci_config = config
     auth_state.oci_key_profile = profile
-    if auth == AuthType.API_KEY:
+    if auth == AuthType.API_KEY and not signer and not signer_callable:
         if os.path.exists(os.path.expanduser(oci_config_location)):
             auth_state.oci_config_path = oci_config_location
         else:
@@ -160,6 +168,7 @@ def set_auth(
     auth_state.oci_signer = signer
     auth_state.oci_signer_callable = signer_callable
     auth_state.oci_signer_kwargs = signer_kwargs
+    auth_state.oci_client_kwargs = client_kwargs
 
 
 def api_keys(
@@ -326,6 +335,7 @@ def default_signer(client_kwargs: Optional[Dict] = None) -> Dict:
     ----------
     client_kwargs : dict
         kwargs that are required to instantiate the Client if we need to override the defaults.
+        Example: client_kwargs = {"timeout": 60}
 
     Returns
     -------
@@ -364,7 +374,10 @@ def default_signer(client_kwargs: Optional[Dict] = None) -> Dict:
         signer_dict = {
             "config": configuration,
             "signer": signer,
-            "client_kwargs": client_kwargs,
+            "client_kwargs": {
+                **(auth_state.oci_client_kwargs or {}),
+                **(client_kwargs or {}),
+            },
         }
         logger.info(f"Using authentication signer type {type(signer)}.")
         return signer_dict
@@ -373,7 +386,10 @@ def default_signer(client_kwargs: Optional[Dict] = None) -> Dict:
             oci_config_location=auth_state.oci_config_path,
             oci_key_profile=auth_state.oci_key_profile,
             oci_config=auth_state.oci_config,
-            client_kwargs=client_kwargs,
+            client_kwargs={
+                **(auth_state.oci_client_kwargs or {}),
+                **(client_kwargs or {}),
+            },
         )
         signer_generator = AuthFactory().signerGenerator(auth_state.oci_iam_type)
         return signer_generator(signer_args).create_signer()
@@ -778,6 +794,9 @@ def __init__(self, **kwargs):
                 a callable object that returns signer
             signer_kwargs: Optional[Dict], default None
                 parameters accepted by the signer
+            client_kwargs: Optional[Dict], default None
+                Additional keyword arguments for initializing the OCI client.
+                Example: client_kwargs = {"timeout": 60}
         """
         self.kwargs = kwargs
 

ads/common/decorator/deprecate.py

@@ -1,25 +1,30 @@
 #!/usr/bin/env python
 # -*- coding: utf-8 -*--
 
-# Copyright (c) 2021, 2022 Oracle and/or its affiliates.
+# Copyright (c) 2021, 2023 Oracle and/or its affiliates.
 # Licensed under the Universal Permissive License v 1.0 as shown at https://oss.oracle.com/licenses/upl/
 
 import warnings
 from enum import Enum
 from functools import wraps
 
 
+class NotSupportedError(Exception):
+    pass
+
+
 class TARGET_TYPE(Enum):
     CLASS = "Class"
     METHOD = "Method"
     ATTRIBUTE = "Attribute"
 
 
 def deprecated(
-    deprecated_in: str,
+    deprecated_in: str = None,
     removed_in: str = None,
     details: str = None,
     target_type: str = None,
+    raise_error: bool = False,
 ):
     """This is a decorator which can be used to mark functions
     as deprecated. It will result in a warning being emitted
@@ -44,14 +49,19 @@ def wrapper(*args, **kwargs):
             else:
                 _target_type = target_type or TARGET_TYPE.METHOD.value
                 target_name = target.__name__
-
-            msg = (
-                f"{_target_type} {target_name} is "
-                f"deprecated in {deprecated_in} and will be "
-                f"removed in {removed_in if removed_in else 'a future release'}."
-                f"{'' if not details else ' ' + details}"
-            )
-            warnings.warn(msg, DeprecationWarning, stacklevel=2)
+            if deprecated_in:
+                msg = (
+                    f"{_target_type} {target_name} is "
+                    f"deprecated in {deprecated_in} and will be "
+                    f"removed in {removed_in if removed_in else 'a future release'}."
+                    f"{'' if not details else ' ' + details}"
+                )
+            else:
+                msg = details
+            if raise_error:
+                raise NotSupportedError(msg)
+            else:
+                warnings.warn(msg, DeprecationWarning, stacklevel=2)
             return target(*args, **kwargs)
 
         return wrapper

ads/common/decorator/runtime_dependency.py

@@ -1,7 +1,7 @@
 #!/usr/bin/env python
 # -*- coding: utf-8; -*-
 
-# Copyright (c) 2021, 2022 Oracle and/or its affiliates.
+# Copyright (c) 2021, 2023 Oracle and/or its affiliates.
 # Licensed under the Universal Permissive License v 1.0 as shown at https://oss.oracle.com/licenses/upl/
 
 """
@@ -63,6 +63,7 @@ class OptionalDependency:
     ONNX = "oracle-ads[onnx]"
     OPTUNA = "oracle-ads[optuna]"
     SPARK = "oracle-ads[spark]"
+    HUGGINGFACE = "oracle-ads[huggingface]"
 
 
 def runtime_dependency(